├── .DS_Store ├── README.md ├── SRGCNN_demo.ipynb └── airbnb └── regression_db.geojson /.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/dizhu-gis/SRGCNN/c17fc33c64b2929cf09c5f2cec57efa5f8c28a1f/.DS_Store -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # SRGCNN 2 | Spatial regression graph convolutional neural networks (SRGCNNs) as a deep learning paradigm that is capable of handling a wide range of geographical tasks 3 | where multivariate geographic data needs spatial regression modeling and prediction. 4 | 5 | Spatial regression analysis conducted in the manner of graph convolutional neural network. 6 | Two versions of SRGCNN model are provided in the initial post: a) global regression model (SRGCNN) and b) geographically weighted regression model (SRGCNN-GW) 7 | 8 | Details can be found in the original paper: 9 | [Zhu, D., Liu, Y., Yao, X., & Fischer, M. M. (2021). Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions. GeoInformatica, 1-32.](https://link.springer.com/article/10.1007/s10707-021-00454-x). 10 | 11 | 12 | 2_SRGCNNs_workflow 13 | 2_SRGCNNs_workflow 14 | 2_SRGCNNs_workflow 15 | --------------------------------------------------------------------------------